Marketing is a main source of income generation as
firms seek to attract web visitors and convert those web visitors into paying
customers. Firms consistently rely on a few marketing methods and overstate the
importance of those methods without understanding how they work together to
convert purchasing behavior. Research by Li & Kannan (2014) helps companies
understand online channels, historical visits using these channels, and how
spillover effects convert visitors into paying customers. They propose a new
model that helps conceptualize the concept.
Even though some companies rely on specific channels
it is the combination of advertising channels that create the marketing mix. It
is difficult for firms to determine which channels work well and which channels
do not effectively contribute to customer conversion rates. Online marketing
will move from $15 billion to $24 billion by 2016 (eMarketer, 2012). The growth
in marketing expenditures will require better analysis of benefits in terms of
attracting the right kinds of customers.
Consumers in the online world may click and browse a
number of different sites before actually visiting a webpage and making a
purchase. Initial exposure and activities are regularly discounted according to
conventional practices such as the last-click analysis. Consumers exposed at
one time to a company or product may not make a purchase until some other point
in time leaving previous exposures uncovered as a source of marketing.
The authors designed a model that helps to analyze
the spillover effects of marketing. Based upon individual-level path data of
customers’ touches their purchase decision hierarchy finds 1) heterogeneity
across customer’s channel use to visit sites, 2) the carryover and spillover impact
of prior marketing interventions that lead to visits, and 3) the conversion of
visits to purchases. The overall approach helps to highlight how online
purchases that use multiple channels mesh together to lead consumers to a
particular site to encourage purchasing behavior.
The model is in alignment with other research
focused on Internet marketing. According to Wiesel, et. al. (2011) there are
three stages to a purchase that include the consideration stage, visit stage,
and purchase stage. In the consideration
stage the customer determines his needs and utilizes different channels to find
information, in the visit stage they visit a website based upon channel
information, and in the purchase stage the customer makes a purchase.
As you can see from the figure the consumer moves
through the consideration, visit and purchase stage by using customer initiated
or firm initiated channels. Customer initiated methods could be direct, referral,
or search engine. Firm initiated methods include things like display ads and
email advertisements that are pushed on the customer. Each of the effects
contributes in a spillover effects that translate into total attractiveness of
making a purchase.
The researchers found that both firm and customer
initiated advertising channels contributes to purchasing behavior in some ways.
The model helps companies determine where their advertising dollars are likely
to receive the highest returns on investment. Paid search engine position is
less effective than originally thought and using emails in combination with
other organic methods helps consumers find the website and subsequently make a purchase.
Understanding how customers find particular products/services and converts them
to make a purchase furthers effective spending of revenue budgets on those
channels that make the best marketing mix.
eMarketer (2012). U.S. Digital Ad
Spending to Top $37 Billion in 2012 as Market Consolidates. Retrieved June 8th,
2014 from http://www.emarketer.com/newsroom/index.php/digital-ad-spending-top-37-billion-2012-market-consolidates/
Li, H. &Kannan, P. (2014). Attributing
conversions in a multichannel online marketing environment: an empirical model
and a field experiment. Journal of
Marketing Research, 51 (1).
Wiesel, T. et. al. (2011). Marketing’s
Profit Impact: Quantifying Online and Off-Line Funnel Progression. Marketing
Science, 30 (4), 604–611.
